Towards a Situated Spatial Epidemiology of Violence: A Placially-Informed Geospatial Analysis of Homicide in Alagoas, Brazil

Blake Byron Walker, Cléssio Moura de Souza, Enrique Pedroso, Ryan S. Lai, Paige Hunter, Jessy Tam, Isaac Cave, David Swanlund and Kevan Guilherme Nóbrega Barbosa
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Blake Byron Walker: Institüt für Geographie, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
Cléssio Moura de Souza: Institüt für Geographie, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
Enrique Pedroso: Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
Ryan S. Lai: Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
Paige Hunter: Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
Jessy Tam: Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
Isaac Cave: Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
David Swanlund: Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
Kevan Guilherme Nóbrega Barbosa: Department for the Professional Master Programme in Health Research, Campus IV, Centro Universitário CESMAC, Macieó 57051-530, Brazil

IJERPH, 2020, vol. 17, issue 24, 1-15

Abstract: This paper presents an empirically grounded call for a more nuanced engagement and situatedness with placial characteristics within a spatial epidemiology frame. By using qualitative data collected through interviews and observation to parameterise standard and spatial regression models, and through a critical interpretation of their results, we present initial inroads for a situated spatial epidemiology and an analytical framework for health/medical geographers to iteratively engage with data, modelling, and the context of both the subject and process of analysis. In this study, we explore the socioeconomic factors that influence homicide rates in the Brazilian state of Alagoas from a critical public health perspective. Informed by field observation and interviews with 24 youths in low-income neighbourhoods and prisons in Alagoas, we derive and critically reflect on three regression models to predict municipal homicide rates from 2016–2020. The model results indicate significant effects for the male population, persons without elementary school completion, households with reported income, divorced persons, households without piped water, and persons working outside their home municipality. These results are situated in the broader socioeconomic context, trajectories, and cycles of inequality in the study area and underscore the need for integrative and contextually engaged mixed method study design in spatial epidemiology.

Keywords: Brazil; GIS; crime; homicide; violence; social determinants; infrastructure; spatial epidemiology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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